code: def test_target_encoder_fit_HaveConstructorSetSmoothingAndMinSamplesLeaf_ExpectUsedInFit(
      self,
  ):
      k = 2
      f = 10
      binary_cat_example = pd.DataFrame(
          {
              "Trend": [
                  "UP",
                  "UP",
                  "DOWN",
                  "FLAT",
                  "DOWN",
                  "UP",
                  "DOWN",
                  "FLAT",
                  "FLAT",
                  "FLAT",
              ],
              "target": [1, 1, 0, 0, 1, 0, 0, 0, 1, 1],
          }
      )
      encoder = encoders.TargetEncoder(
          cols=["Trend"], min_samples_leaf=k, smoothing=f
      )
      encoder.fit(binary_cat_example, binary_cat_example["target"])
      trend_mapping = encoder.mapping["Trend"]
      ordinal_mapping = encoder.ordinal_encoder.category_mapping[0][
          "mapping"
      ]
  
      self.assertAlmostEqual(
          0.4125, trend_mapping[ordinal_mapping.loc["DOWN"]], delta=1e-4
      )
      self.assertEqual(0.5, trend_mapping[ordinal_mapping.loc["FLAT"]])
      self.assertAlmostEqual(
          0.5874, trend_mapping[ordinal_mapping.loc["UP"]], delta=1e-4
      )
  
imports: import pandas
  from unittest import TestCase
  import tests.helpers
  import numpy
  from category_encoders.datasets import load_postcodes, load_compass
  import category_encoders
label_desc: Use image node_id 3 for calling the TestTargetEncoder obj's underlying member method code with example usage: obj.test_target_encoder_fit_HaveConstructorSetSmoothingAndMinSamplesLeaf_ExpectUsedInFit() without return types